code: def test_num_symbols(sparse_data):
      X, y, categorical = sparse_data
      mf = meta_features.helper_functions["NumSymbols"](
          X, y, logging.getLogger("Meta"), categorical
      )
  
      symbol_frequency = [
          2,
          0,
          6,
          0,
          1,
          3,
          0,
          0,
          3,
          1,
          0,
          0,
          0,
          1,
          0,
          0,
          0,
          0,
          0,
          0,
          0,
          0,
          0,
          2,
          0,
          0,
          0,
          0,
          1,
          1,
          2,
          2,
      ]
      assert mf.value == symbol_frequency
  
imports: import logging
  import os
  import arff
  import numpy
  from scipy import sparse
  from sklearn.impute import SimpleImputer
  from sklearn.preprocessing import StandardScaler
  import autosklearn.metalearning.metafeatures.metafeatures
  from autosklearn.pipeline.components.data_preprocessing.feature_type import FeatTypeSplit
  import pytest
label_desc: Use image node_id 10 for calling a global function with example usage: test_num_symbols(sparse_data) without return types